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DBMS > FatDB vs. Microsoft Azure Table Storage vs. Spark SQL vs. TerarkDB

System Properties Comparison FatDB vs. Microsoft Azure Table Storage vs. Spark SQL vs. TerarkDB

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.A Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument store
Key-value store
Wide column storeRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#367  Overall
#56  Key-value stores
Websiteazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperFatCloudMicrosoftApache Software FoundationByteDance, originally Terark
Initial release2012201220142016
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaC++
Server operating systemsWindowshostedLinux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesnonono
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
RESTful HTTP APIJDBC
ODBC
C++ API
Java API
Supported programming languagesC#.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyes infovia applicationsnonono
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights based on private key authentication or shared access signaturesnono

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More resources
FatDBMicrosoft Azure Table StorageSpark SQLTerarkDB
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